Low Flows Modeling Using Temperature and Rainfall Climatic Variables (Case Study: Eskandari Basin, Esfahan Province)

By development numerical models for prediction of climate variables، analyzing the effects of climate changing phenomena on water resources has been provided more. General circulation models of atmosphere are known as the best numerical models for predicting future climate. These models، considering production and emission of greenhouse gases scenarios، predict temperature and rainfall variables. In this study، regarding low stream regression، using temperature and rainfall parameters in monthly and seasonal scales، are produced in a seven-day manner in different return periods. As a result، relative error for 5، 10 and 20-years-lasting return periods، are 1. 6، 2. 2 and 0. 13 percent، which have less error than other training models. Using outputs of GCM (HadCM3) models، temperature and rainfall variables for three periods of (2011-2040)، (2041-2070) and (2071-2099) are predicted. Q7،T model is performed for each 30-year period and minimum streams are estimated for these periods.